Search results for: decision making loop

Authors: Silvija Šiljeg, Ante Šiljeg, Branko Cavrić

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Housing is considered as a basic human need and important component of the quality of life (QoL) in urban areas worldwide. In contemporary housing studies, the concept of the quality of housing (QoH) is considered as a multi-dimensional and multi-disciplinary field. It emphasizes connection between various aspects of the QoL which could be measured by quantitative and qualitative indicators at different spatial levels (e.g. local, city, metropolitan, regional). The main goal of this paper is to examine the QoH and compare results of quantitative analysis with the clutter land use categories derived for selected local communities in Croatian Coastal City of Zadar. The qualitative housing analysis based on the four housing indicators (out of total 24 QoL indicators) has provided identification of the three Zadar’s local communities with the highest estimated QoH ranking. Furthermore, by using GIS overlay techniques, the QoH was merged with the urban environment analysis and introduction of spatial metrics based on the three categories: the element, class and environment as a whole. In terms of semantic-content analysis, the research has also generated a set of indexes suitable for evaluation of “housing state of affairs” and future decision making aiming at improvement of the QoH in selected local communities.

Keywords: housing, quality, indicators, indexes, urban environment, GIS, element, class

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Authors: Umesh Kumar Singh, Chanchala Joshi

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With increasing dependency on IT infrastructure, the main objective of a system administrator is to maintain a stable and secure network, with ensuring that the network is robust enough against malicious network users like attackers and intruders. Security risk management provides a way to manage the growing threats to infrastructures or system. This paper proposes a framework for risk level estimation which uses vulnerability database National Institute of Standards and Technology (NIST) National Vulnerability Database (NVD) and the Common Vulnerability Scoring System (CVSS). The proposed framework measures the frequency of vulnerability exploitation; converges this measured frequency with standard CVSS score and estimates the security risk level which helps in automated and reasonable security management. In this paper equation for the Temporal score calculation with respect to availability of remediation plan is derived and further, frequency of exploitation is calculated with determined temporal score. The frequency of exploitation along with CVSS score is used to calculate the security risk level of the system. The proposed framework uses the CVSS vectors for risk level estimation and measures the security level of specific network environment, which assists system administrator for assessment of security risks and making decision related to mitigation of security risks.

Keywords: CVSS score, risk level, security measurement, vulnerability category

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Authors: Awe Ayodeji Samson, Adeuja Yetunde Omowunmi

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Corruption is a ‘monster’ that can consume a whole nation, continent and even the world if it is not destroyed while it is still immature; It grows in the mind of the people, takes over their thinking and guides their decision-making process. Corruption snowballs into socio-economic catastrophe that might be difficult to deal with. Corruption which is a disease of the mind can be alleviated in Africa and the world at large by transforming a Corruption-Prone Mind to a Corruption-Immune Mind and to achieve this, we have to change our value system because the use of anti-graft agencies alone is not enough. Therefore, we have to fight corruption from the inside and the outside. Value System is the principle of right and wrong that are accepted by an individual or a social group; the reviewing and reordering of our value system is the solution to the problem of corruption as proposed by this research because the African society has become a ‘Money and Power Driven Society’ where the ‘I am worth concept’ which is a problematic concept has created an ‘Aggressive Society’ with grasping and money-grabbing individuals. We place more priority on money and the display of opulence. Hence, this has led to a ‘Triangular Society’ where minority is lavishing in plenty and majority is gasping for little. The get rich quick syndrome, the ethnicity syndrome, weakened educational system are signs of the prevalence of corruption in Africa This research has analyzed role and impact of the change in our value system in the fight against corruption in Africa and has therefore proposed the change in our value system as the way forward in the fight against corruption in Africa.

Keywords: corruption-prone mind, corruption-immune mind, triangular society, aggressive society, money and power-driven society

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Authors: Vesna Karapetkovska Hristova, M. Ayaz Ahmad, Julijana Tomovska, Biljana Bogdanova Popov, Blagojce Najdovski

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The average total concentrations of heavy metals; (cadmium [Cd], copper [Cu], nickel [Ni], lead [Pb], and zinc [Zn]) were analyzed in soil and vegetables samples collected from the different region of Macedonia during the years 2010-2012. Basic soil properties such as pH, organic matter and clay content were also included in the study. The average concentrations of Cd, Cu, Ni, Pb, Zn in the A horizon (0-30 cm) of agricultural soils were as follows, respectively: 0.25, 5.3, 6.9, 15.2, 26.3 mg kg-1 of soil. We have found that neural networking model can be considered as a tool for prediction and spatial analysis of the processes controlling the metal transfer within the soil-and vegetables. The predictive ability of such models is well over 80% as compared to 20% for typical regression models. A radial basic function network reflects good predicting accuracy and correlation coefficients between soil properties and metal content in vegetables much better than the back-propagation method. Neural Networking / soft computing can support the decision-making processes at different levels, including agro ecology, to improve crop management based on monitoring data and risk assessment of metal transfer from soils to vegetables.

Keywords: soft computing approach, total concentrations, heavy metals, agricultural soils

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Authors: Mohammed Buhaya

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Purpose: The purpose of this study is to analyze the decision, implementation process and the outcomes of the introduction of the balanced scorecard in a developing country having particular regard to the impacts of agency and institutional, endogenous and exogenous. Design/methodology/approach: This study builds on a longitudinal explanatory case study, an institutional framework, especially Ter-Bogt and Scapens (2014) framework. Findings: Empirical findings drawn from a telecom company indicate that the dynamics of change of the company are influenced by the interconnection of external institutions and the company's situation and internal institutions encompassing issues of power, politics, and culture. Organizational practice introduced to secure external legitimacy is not always the case. The adoption of the balanced scorecard was the instrumental manner and had revolutionary change. Originality/value: In contrast to much previous research on management accounting practice, the paper analyses the process of change in one of developing country. The study also sheds new light on the power of religion as one of institutional logics and how this logic rises to potential to influence management accounting change among actors and achieving the company’s targets. This paper highlights how the culture and values can play a vital role in making the process of change smoother.

Keywords: balanced scorecard, institutional, management accounting practice, rules, and routines

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Authors: Giuseppe Timperio, Robert De Souza

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The combination of factors such as temperamental climate change, rampant urbanization of risk exposed areas, political and social instabilities, is posing an alarming base for the further growth of number and magnitude of humanitarian crises worldwide. Given the unique features of humanitarian supply chain such as unpredictability of demand in space, time, and geography, spike in the number of requests for relief items in the first days after the calamity, uncertain state of logistics infrastructures, large volumes of unsolicited low-priority items, a proactive approach towards design of disaster response operations is needed to achieve high agility in mobilization of emergency supplies in the immediate aftermath of the event. This paper is an attempt in that direction, and it provides decision makers with crucial strategic insights for a more effective network design for disaster response. Decision sciences and ICT are integrated to analyse the robustness and resilience of a prepositioned network of emergency strategic stockpiles for a real-life case about Indonesia, one of the most vulnerable countries in Asia-Pacific, with the model being built upon a rich set of quantitative data. At this aim, a network optimization approach was implemented, with several what-if scenarios being accurately developed and tested. Findings of this study are able to support decision makers facing challenges related with disaster relief chains resilience, particularly about optimal configuration of supply chain facilities and optimal flows across the nodes, while considering the network structure from an end-to-end in-country distribution perspective.

Keywords: disaster preparedness, humanitarian logistics, network optimization, resilience

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Authors: M. I. Abdelhamid, A. O. Ghallab, R. S. Ettouney, M. A. El-Rifai

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An optimization scheme based on COM server is suggested for communication between Genetic Algorithm (GA) toolbox of MATLAB and Aspen HYSYS. The structure and details of the proposed framework are discussed. The power of the developed scheme is illustrated by its application to the optimization of a recently developed natural gas liquefaction process in which Aspen HYSYS was used for minimization of the power consumption by optimizing the values of five operating variables. In this work, optimization by coupling between the GA in MATLAB and Aspen HYSYS model of the same process using the same five decision variables enabled improvements in power consumption by 3.3%, when 77% of the natural gas feed is liquefied. Also on inclusion of the flow rates of both nitrogen and carbon dioxide refrigerants as two additional decision variables, the power consumption decreased by 6.5% for a 78% liquefaction of the natural gas feed.

Keywords: stranded gas liquefaction, genetic algorithm, COM server, single nitrogen expansion, carbon dioxide pre-cooling

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Authors: Nadia Arikat, Katharine Blain

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During the worst of the COVID pandemic, only essential treatment was provided for patients needing urgent care. With the prolonged extent of the pandemic, there has been a return to more routine referrals for paediatric dentistry advice and treatment for specialist conditions. However, some of these patients and/or their carers may have significant medical issues meaning that attending in-person appointments carries additional risks. This poses an ethical dilemma for clinicians. This project looks at how a secure video conferencing platform (“Near Me”) has been used to assess the need and urgency for in-person new patient visits, particularly for patients and families with additional risks. “Near Me” is a secure online video consulting service used by NHS Scotland. In deciding whether to bring a new patient to the hospital for an appointment, the clinical condition of the teeth together with the urgency for treatment need to be assessed. This is not always apparent from the referral letter. In addition, it is important to judge the risks to the patients and carers of such visits, particularly if they have medical issues. The use and effectiveness of “Near Me” consultations to help decide whether vulnerable paediatric patients should have in-person appointments will be illustrated and discussed using two families: one where the child is medically compromised (Alagille syndrome with previous liver transplant), and the other where there is a medically compromised parent (undergoing chemotherapy and a bone marrow transplant). In both cases, it was necessary to take into consideration the risks and moral implications of requesting that they attend the dental hospital during a pandemic. The option of remote consultation allowed further clinical information to be evaluated and the families take part in the decision-making process about whether and when such visits should be scheduled. These cases will demonstrate how medically compromised patients (or patients with vulnerable carers), could have their dental needs assessed in a socially distanced manner by video consultation. Together, the clinician and the patient’s family can weigh up the risks, with regards to COVID-19, of attending for in-person appointments against the benefit of having treatment. This is particularly important for new paediatric patients who have not yet had a formal assessment. The limitations of this technology will also be discussed. It is limited by internet availability, the strength of the connection, the video quality and families owning a device which allows video calls. For those from a lower socio-economic background or living in some rural areas, this may not be possible or limit its usefulness. For the two patients discussed in this project, where the urgency of their dental condition was unclear, video consultation proved beneficial in deciding an appropriate outcome and preventing unnecessary exposure of vulnerable people to a hospital environment during a pandemic, demonstrating the usefulness of such technology when it is used appropriately.

Keywords: COVID-19, paediatrics, triage, video consultations

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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Authors: Anurag Gaur, Neha Sharma

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In this work, we have synthesized BaTiO3 via sol gel method by sintering at different temperatures (600-1000 0C) and studied their structural, optical and ferroelectric properties through X-Ray diffraction (XRD), UV-Vis spectrophotometer and PE Loop Tracer. X-Ray diffraction patterns of barium titanate samples show that the peaks of the diffractogram are successfully indexed with the tetragonal structure of BaTiO3 along with some minor impurities of BaCO3. The optical band gap calculated through UV Visible spectrophotometer varies from 4.37 to 3.80 eV for the samples sintered at 600 to 1000 0 C, respectively. The particle size calculated through transmission electron microscopy varies from 20 to 60 nm for the samples sintered at 600 to 1000 0C, respectively. Moreover, it has been observed that the ferroelectricity reduces as we increase the sintering temperature.

Keywords: nanostructures, ferroelectricity, sol-gel method, diffractogram

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Authors: Jamilah Halina Abdul Halim, Norsiah Hassan, Azlina Aziz, Norhayati Mat Wajid, Mohd Saipul Asrafi

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There are various types of vertical greenery system (VGS) in Malaysia, but none is installed at government buildings, although the government is looking into energy efficient building design. This is due to lack of technical information that focus on the maintenance and care, issues, and challenges face by vertical greenery system under tropical climate conditions. This research aim to identify issues in implementation of vertical greenery system on existing government building in Malaysia. The methodology used are literature reviews (desktop study), observation on sites, and case studies. Initial findings indicates that design and maintenance issues of vertical greenery system are the main challenges faced mainly by designer, especially those who involved in decision-making process. It can be concluded that orientation, openings, maintenance, performance, longevity, structural load, access, wind resistance, design failure, system failure, and lack of maintenance foresight are the main factors that need to be considered. These factors should be holistically aligned towards the economic cost, effective time, and quality design in implementation of vertical greenery system on existing government building. A comprehensive implementation of vertical greenery system will lead to greater sustainable investment for government buildings and responsive action to climate change.

Keywords: issues, government building, maintenance, vertical greenery system

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: Eurico Lima Basto, Ofélia Pinto, Anabela Silva, Amélia Ferreira-Da-Silva

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The purpose if this study is two-fold: on the one hand, to identify the accounting information systems implemented in third sector organizations, as well as its components, its tools and the decisions and control purposes they serve; on the other hand, and by confronting these two theories - institutional theory versus rational choice – we intent to go further by understanding the reasons behind the adoption of the aforementioned tools. Data has been collected from third sector organizations operating in Portugal. Our sample includes all juridical types of organizations such as foundations, cooperative, associations or private institutions of social solidarity. The questionnaire contained sixteen close-ended questions and four open-questions. Results confirm the theoretical perspective of institutionalism. Most third sector organizations operating in Portugal implemented only traditional accounting tools like standard accounting statements, cost accounting, budgeting. Moreover, there is clear evidence that the decisions about the implementation of these tools were coercive oriented. With this study it is intended to contribute to a better understanding of the context of third sector organizations in Portugal, in particular the role that accounting plays in this sector, with a special focus on management accounting tools, and the factors that influence their use and the degree of their usefulness in the process of decision making.

Keywords: third sector, accounting tools, institutional theory, Portugal, descriptive research

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Authors: Roseanne Sharon Borromeo, Mariana Carvalho, Mariia Karizhenskaia

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Healthcare providers need to comprehend cultural diversity for optimal patient-centered care, especially near the end of life. Although a universal method for navigating cultural differences would be ideal, culture’s high complexity makes this strategy impossible. Adding cultural humility, a process of self-reflection to understand personal and systemic biases and humbly acknowledging oneself as a learner when it comes to understanding another's experience leads to a meaningful process in palliative care generating respectful, honest, and trustworthy relationships. This study is a systematic review of the literature on cultural humility in palliative care research and best practices. Race, religion, language, values, and beliefs can affect an individual’s access to palliative care, underscoring the importance of culture in palliative care. Cultural influences affect end-of-life care perceptions, impacting bereavement rituals, decision-making, and attitudes toward death. Cultural factors affecting the delivery of care identified in a scoping review of Canadian literature include cultural competency, cultural sensitivity, and cultural accessibility. As the different parts of the world become exponentially diverse and multicultural, healthcare providers have been encouraged to give culturally competent care at the bedside. Therefore, many organizations have made cultural competence training required to expose professionals to the special needs and vulnerability of diverse populations. Cultural competence is easily standardized, taught, and implemented; however, this theoretically finite form of knowledge can dangerously lead to false assumptions or stereotyping, generating poor communication, loss of bonds and trust, and poor healthcare provider-patient relationship. In contrast, Cultural humility is a dynamic process that includes self-reflection, personal critique, and growth, allowing healthcare providers to respond to these differences with an open mind, curiosity, and awareness that one is never truly a “cultural” expert and requires life-long learning to overcome common biases and ingrained societal influences. Cultural humility concepts include self-awareness and power imbalances. While being culturally competent requires being skilled and knowledgeable in one’s culture, being culturally humble involves the sometimes-uncomfortable position of healthcare providers as students of the patient. Incorporating cultural humility emphasizes the need to approach end-of-life care with openness and responsiveness to various cultural perspectives. Thus, healthcare workers need to embrace lifelong learning in individual beliefs and values on suffering, death, and dying. There have been different approaches to this as well. Some adopt strategies for cultural humility, addressing conflicts and challenges through relational and health system approaches. In practice and research, clinicians and researchers must embrace cultural humility to advance palliative care practices, using qualitative methods to capture culturally nuanced experiences. Cultural diversity significantly impacts patient-centered care, particularly in end-of-life contexts. Cultural factors also shape end-of-life perceptions, impacting rituals, decision-making, and attitudes toward death. Cultural humility encourages openness and acknowledges the limitations of expertise in one’s culture. A consistent self-awareness and a desire to understand patients’ beliefs drive the practice of cultural humility. This dynamic process requires practitioners to learn continuously, fostering empathy and understanding. Cultural humility enhances palliative care, ensuring it resonates genuinely across cultural backgrounds and enriches patient-provider interactions.

Keywords: cultural competency, cultural diversity, cultural humility, palliative care, self-awareness

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Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

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Planning models for fresh products is a very useful tool for improving the net profits. To get an efficient supply chain model, several functions should be considered to get a complete simulation of several operational units. We consider a linear programming model to help farmers to decide if it is convenient to choose what area should be planted for three kinds of export fruits considering their future investment. We consider area, investment, water, productivity minimal unit, and harvest restrictions to develop a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability, and initial investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market. Also, this tool help to support decisions for government and individual farmers.

Keywords: mixed integer problem, fresh fruit production, support decision model, agricultural and biosystems engineering

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Authors: Cyril Mae B. Mationg, Alexa T. Belizar, Vethany B. Bellen

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This study aims to determine the use of coconut husks and sugarcane bagasse as natural components in making water-resistant tote bags. The study consists of three concentrations: 70% Coconut Husk - 30% Sugarcane Bagasse, 70% cellulose, and 30% cellulose. The results of these tests revealed that, out of the three concentration concentrations, the one consisting of 70% Coconut Husk and 30% sugarcane bagasse exhibited superior performance in breaking capacity and water penetration. During tensile strength testing, the coconut husk and sugarcane bagasse withstood a force of 207.7 Newtons (N) in the machine direction and 216.5 N in the cross-machine direction.

Keywords: coconut husk, sugarcane bagasse, tote bags, water resistance

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Authors: Jyh Sheen, Yang-Hung Cheng

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This paper presents a design of a microstrip bandpass filter with a compact size and wide stopband by using 0.15-μm GaAs pHEMT process. The wide stop band is achieved by suppressing the first and second harmonic resonance frequencies. The slow-wave coupling stepped impedance resonator with cross coupled structure is adopted to design the bandpass filter. A two-resonator filter was fabricated with 13.5GHz center frequency and 11% bandwidth was achieved. The devices are simulated using the ADS design software. This device has shown a compact size and very low insertion loss of 2.6 dB. Microstrip planar bandpass filters have been widely adopted in various communication applications due to the attractive features of compact size and ease of fabricating. Various planar resonator structures have been suggested. In order to reach a wide stopband to reduce the interference outside the passing band, various designs of planar resonators have also been submitted to suppress the higher order harmonic frequencies of the designed center frequency. Various modifications to the traditional hairpin structure have been introduced to reduce large design area of hairpin designs. The stepped-impedance, slow-wave open-loop, and cross-coupled resonator structures have been studied to miniaturize the hairpin resonators. In this study, to suppress the spurious harmonic bands and further reduce the filter size, a modified hairpin-line bandpass filter with cross coupled structure is suggested by introducing the stepped impedance resonator design as well as the slow-wave open-loop resonator structure. In this way, very compact circuit size as well as very wide upper stopband can be achieved and realized in a Roger 4003C substrate. On the other hand, filters constructed with integrated circuit technology become more attractive for enabling the integration of the microwave system on a single chip (SOC). To examine the performance of this design structure at the integrated circuit, the filter is fabricated by the 0.15 μm pHEMT GaAs integrated circuit process. This pHEMT process can also provide a much better circuit performance for high frequency designs than those made on a PCB board. The design example was implemented in GaAs with center frequency at 13.5 GHz to examine the performance in higher frequency in detail. The occupied area is only about 1.09×0.97 mm2. The ADS software is used to design those modified filters to suppress the first and second harmonics.

Keywords: microstrip resonator, bandpass filter, harmonic suppression, GaAs

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Authors: Luís Pina

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The conservation of marine biodiversity keeps ecosystems in balance and ensures the sustainable use of resources. In this context, technological resources have been used for monitoring marine species to allow biologists to obtain data in real-time. There are different mobile applications developed for data collection for monitoring purposes, but these systems are designed to be utilized only on third-generation (3G) phones or smartphones with Internet access and in rural parts of the developing countries, Internet services and smartphones are scarce. Thus, the objective of this work is to develop a system to monitor marine turtles using Unstructured Supplementary Service Data (USSD), which users can access through basic mobile phones. The system aims to improve the data collection mechanism and enhance the effectiveness of current systems in monitoring sea turtles using any type of mobile device without Internet access. The system will be able to report information related to the biological activities of marine turtles. Also, it will be used as a platform to assist marine conservation entities to receive reports of illegal sales of sea turtles. The system can also be utilized as an educational tool for communities, providing knowledge and allowing the inclusion of communities in the process of monitoring marine turtles. Therefore, this work may contribute with information to decision-making and implementation of contingency plans for marine conservation programs.

Keywords: GSM, marine biology, marine turtles, unstructured supplementary service data (USSD)

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Authors: P. T. Collett, M. Kershaw

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Introduction: The discussion regarding which method of anesthesia provides better results for lower limb arthroplasty is a continuing debate. Multiple meta-analysis has been performed with no clear consensus. The current recommendation is to use neuraxial anesthesia for lower limb arthroplasty; however, the evidence to support this decision is weak. The Enhanced Recovery After Surgery (ERAS) society has recommended, either technique can be used as part of a multimodal anesthetic regimen. A local study was performed to see if the current anesthetic practice correlates with the current recommendations and to evaluate the efficacy of the different techniques utilized. Method: 90 patients who underwent total hip or total knee replacements at Nevill Hall Hospital between February 2019 to July 2019 were reviewed. Data collected included the anesthetic technique, day one opiate use, pain score, and length of stay. The data was collected from anesthetic charts, and the pain team follows up forms. Analysis: The average of patients undergoing lower limb arthroplasty was 70. Of those 83% (n=75) received a spinal anaesthetic and 17% (n=15) received a general anaesthetic. For patients undergoing knee replacement under general anesthetic the average day, one pain score was 2.29 and 1.94 if a spinal anesthetic was performed. For hip replacements, the scores were 1.87 and 1.8, respectively. There was no statistical significance between these scores. Day 1 opiate usage was significantly higher in knee replacement patients who were given a general anesthetic (45.7mg IV morphine equivalent) vs. those who were operated on under spinal anesthetic (19.7mg). This difference was not noticeable in hip replacement patients. There was no significant difference in length of stay between the two anesthetic techniques. Discussion: There was no significant difference in the day one pain score between the patients who received a general or spinal anesthetic for either knee or hip replacements. The higher pain scores in the knee replacement group overall are consistent with this being a more painful procedure. This is a small patient population, which means any difference between the two groups is unlikely to be representative of a larger population. The pain scale has 4 points, which means it is difficult to identify a significant difference between pain scores. Conclusion: There is currently little standardization between the different anesthetic approaches utilized in Nevill Hall Hospital. This is likely due to the lack of adherence to a standardized anesthetic regimen. In accordance with ERAS recommends a standard anesthetic protocol is a core component. The results of this study and the guidance from the ERAS society will support the implementation of a new health board wide ERAS protocol.

Keywords: anaesthesia, orthopaedics, intensive care, patient centered decision making, treatment escalation

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Authors: Salima Smiti, Ines Gasmi, Makram Soui

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Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

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Authors: Ming-Kwei Lee, Chih-Feng Yen

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The electrical characteristics of liquid phase deposited silicon oxynitride film on ammonium sulfide treated p-type (100) gallium arsenide substrate were investigated. Hydrofluosilicic acid, ammonia and boric acid aqueous solutions were used as precursors. The electrical characteristics of silicon oxynitride film are much improved on gallium arsenide substrate with ammonium sulfide treatment. With post-metallization annealing, hydrogen ions can further passivate defects in SiON/GaAs film and interface. The leakage currents can reach 7.1 × 10-8 and 1.8 × 10-7 at ± 2 V. The dielectric constant and effective oxide charges are 5.6 and -5.3 × 1010 C/cm2, respectively. The hysteresis offset of hysteresis loop is merely 0.09 V.

Keywords: liquid phase deposition, SiON, GaAs, PMA, (NH4)2S

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Authors: Reyhaneh Saeedi

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Iran is one of the regions which are most prone for earthquakes annually having a large number of financial and mortality and financial losses. Every year around the world, a large number of people lose their home and life due to natural disasters such as earthquakes. It is necessary to provide and specify some suitable places for settling the homeless people before the occurrence of the earthquake, one of the most important factors in crisis planning and management. Some of the natural disasters can be Modeling and shown by Geospatial Information System (GIS). By using GIS, it would be possible to manage the spatial data and reach several goals by making use of the analyses existing in it. GIS has a determining role in disaster management because it can determine the best places for temporary resettling after such a disaster. In this research QuantumGIS software is used that It is an OpenSource software so that easy to access codes and It is also free. In this system, AHP method is used as decision model and to locate the best places for temporary resettling, is done based on the related organizations criteria with their weights and buffers. Also in this research are made the buffer layers of criteria and change them to the raster layers. Later on, the raster layers are multiplied on desired weights then, the results are added together. Eventually, there are suitable places for resettling of victims by desired criteria by different colors with their optimum rate in QuantumGIS platform.

Keywords: disaster management, temporary resettlement, earthquake, QuantumGIS

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Authors: Nayden Takev, Remy van Leeuwen, Shiva Chotoe, Hani Alers, Xiao Peng

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Citizens, businesses, and public authorities all around the world are becoming aware of the impact that they have on the environment. Currently, climate change is an apparent cause to urge everyone to act and move to sustainable energy solutions. After the Paris Climate Agreement, every country has thought of a way to cut down carbon emissions. The Netherlands formulated the National Climate Agreement. “The government’s central goal with the National Climate Agreement is to reduce greenhouse gas emissions in the Netherlands by 49% compared to 1990 levels. At a European level, the government is advocating a 55% reduction of greenhouse gas emissions by 2030.” [5]. From a survey of the CBS, it is apparent that citizens are not putting in as much effort into the transition to sustainable energy as the government would like them to. After analysing the data, it became clear that the citizens miss the motivation to switch to sustainable energy because they do not believe it is urgent at this point and it is too expensive for them [2]. This needs to be changed. The citizens need to be aware of their impact on the climate and the advantages that this process will bring them. For example, the implementation of smart home displays 4 for real time energy measuring will give the citizens an overview of their energy usage so they are aware of the impact they have. Researchers have also found that the citizens must be included in the decision-making aimed at changing their behaviour [4, 3, 1]. In the future, the government will need to include the citizens when they create campaigns, strategies or introduce new policies [7, 6]. By including and informing the citizens about the policies it will be more attractive for them to choose sustainable energy. However, is all of this enough to motivate the citizens towards energy transition? Or are there other and better ways to do it?

Keywords: Awereness, Energy Transition, Netherlands, citizens

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Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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Authors: Ioana Pisica, Dimitrios Gkritzapis

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The significance of UAS in scientific applications has been amply demonstrated in recent years. The combinations of portability and quasi-static positioning by means of flying in close loop path make them versatile and efficient in the inspection of power systems infrastructure. In this paper, we critically assess several platforms and sensor capabilities to identify their pros and cons in relation to the power systems assets to be monitored. In this respect, it is paramount the flights to be conducted by using UAS which bear certain suitable features, such as responsive and easy control, video capturing in real time, autonomous routing of pre-planned flight programming with differentiating payloads. The outcome of this research is a set of optimal requirements for power system assets monitoring with UAS.

Keywords: platforms, power system, sensors, UAVs

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Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

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3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

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Authors: Jung-Min Yang

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A method of tolerating input faults for input/state asynchronous sequential machines is proposed. A corrective controller is placed in front of the considered asynchronous machine to realize model matching with a reference model. The value of the external input transmitted to the closed-loop system may change by fault. We address the existence condition for the controller that can counteract adverse effects of any input fault while maintaining the objective of model matching. A design procedure for constructing the controller is outlined. The proposed reachability condition for the controller design is validated in an illustrative example.

Keywords: asynchronous sequential machines, corrective control, fault tolerance, input faults, model matching

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Authors: Tris Kee

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As the urban design discipline develops renewed interests in participatory design and collaborative place-making, it becomes critical to review the potential and limitations in current processes to ensure a sustainable method for future development.This paper explores how collaborative design can be a key to future sustainable urban development through two case studies from Asia.The process involves a multi-disciplinary collaboration and an innovative learning process by sharing ideas as well as careful consideration on social, economic and political circumstances among government and district stakeholders.This intrinsic proposition of innovative participatory planning implies interdisciplinary collaboration between professionals and local residents to integrate knowledge into new urban place-making thinking.Design innovation in contemporary society can manifest itself in the discourse sustainable urban development by bottom-up planning and community driven design. This paper examines the emerging design pedagogy which promotes interdisciplinary coalition of professionals and local stakeholders in community development as an innovative design rubric to create a sustainable urban approach.Through two case studies in Hong Kong, this paper reviews and critically evaluates the process of how the notion of sustainable development in contemporary urban planning theory is underpinned by the collaborative design practice.

Keywords: collaborative design, design innovation, sustainable development, urban development

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Rawan Hakawati, Beatrice Smyth, David Rooney, Geoffrey McCullough

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Targets have been set in the EU to increase the share of renewable energy consumption to 20% by 2020, but developments have not occurred evenly across the member states. Northern Ireland is almost 90% dependent on imported fossil fuels. With such high energy dependency, Northern Ireland is particularly susceptible to the security of supply issues. Linked to fossil fuels are greenhouse gas emissions, and the EU plans to reduce emissions by 20% by 2020. The use of indigenously produced biomass could reduce both greenhouse gas emissions and external energy dependence. With a wide range of both crop and waste feedstock potentially available in Northern Ireland, anaerobic digestion has been put forward as a possible solution for renewable energy production, waste management, and greenhouse gas reduction. Not all feedstock, however, is the same, and an understanding of feedstock suitability is important for both plant operators and policy makers. The aim of this paper is to investigate biomass suitability for anaerobic digestion in Northern Ireland. It is also important that decisions are based on solid scientific evidence. For this reason, the methodology used is multi-criteria decision matrix analysis which takes multiple criteria into account simultaneously and ranks alternatives accordingly. The model uses the weighted sum method (which follows the Entropy Method to measure uncertainty using probability theory) to decide on weights. The Topsis method is utilized to carry out the mathematical analysis to provide the final scores. Feedstock that is currently available in Northern Ireland was classified into two categories: wastes (manure, sewage sludge and food waste) and energy crops, specifically grass silage. To select the most suitable feedstock, methane yield, feedstock availability, feedstock production cost, biogas production, calorific value, produced kilowatt-hours, dry matter content, and carbon to nitrogen ratio were assessed. The highest weight (0.249) corresponded to production cost reflecting a variation of £41 gate fee to 22£/tonne cost. The weights calculated found that grass silage was the most suitable feedstock. A sensitivity analysis was then conducted to investigate the impact of weights. The analysis used the Pugh Matrix Method which relies upon The Analytical Hierarchy Process and pairwise comparisons to determine a weighting for each criterion. The results showed that the highest weight (0.193) corresponded to biogas production indicating that grass silage and manure are the most suitable feedstock. Introducing co-digestion of two or more substrates can boost the biogas yield due to a synergistic effect induced by the feedstock to favor positive biological interactions. A further benefit of co-digesting manure is that the anaerobic digestion process also acts as a waste management strategy. From the research, it was concluded that energy from agricultural biomass is highly advantageous in Northern Ireland because it would increase the country's production of renewable energy, manage waste production, and would limit the production of greenhouse gases (current contribution from agriculture sector is 26%). Decision-making methods based on scientific evidence aid policy makers in classifying multiple criteria in a logical mathematical manner in order to reach a resolution.

Keywords: anaerobic digestion, biomass as feedstock, decision matrix, renewable energy

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